(1) Field of the Invention
The present invention relates generally to systems and methods for active sonar systems and, more particularly, to a sonar system and method for improved active sonar detection by accurate estimation of the channel/target nonlinear response function.
(2) Description of the Prior Art
Active sonar signal propagation and reflection has intrinsic properties that are noticeably affected by the channel and/or target characteristics. Often, one knows, through measurements, the signal transmitted into the propagation channel and the waveform at the receiver output. The difficulty is to accurately measure and estimate what happens between the excitation input and output.
Signal distortion in an active sonar system may arise for many reasons such as, for example, shallow basins with nonlinear boundary conditions, irregular sea bottoms and surface interactions, bubble formations and nonlinear scattering within the propagation channel, reverberation, nonhomogeneities in sound speed propagation, inelastic target response, target scattering profiles, multipath reflections, additive noise generated by waves, transmission losses, changing distances from the target, and the like.
Active sonar as used herein refers to sonar systems that utilize radiating acoustic sources to probe an area to be searched so as to acoustically illuminate the submerged object. One example of this type of sonar system is a conventional sonar device, wherein a highly directional beam of sonic energy periodically radiates from a scanning transducer, which in turn operates as a receiver to detect echoes reflected from any object(s) within the propagation channel. Modern active sonar systems commonly provide multibeam capabilities as well. Active sonar signals can have relatively high transmission losses which increase as a function of the frequency of the propagated energy.
A large number of active sonar data processing techniques rely on linearity in an acoustic signature (e.g., temporal fluctuations, power spectra) for extracting and identifying information about a particular target illuminated by the active transmission. However, if linear techniques are applied to a target-of-interest in which the target and/or channel response is actually nonlinear, then subsequent purely linear processing of these data leads to results that are incorrect and can be misleading.
Various inventors have attempted to solve the above and related problems as evidenced by the following patents.
U.S. Pat. No. 6,285,972 B1, issued Sep. 4, 2001, to A. J. Barber, discloses a method for generating an improved nonlinear system model that includes generating a linear system model and using a response therefrom to generate the nonlinear system model. A method and system for generating drive signals for a test system uses the improved nonlinear system model or a conventional nonlinear system model.
U.S. Pat. No. 6,327,315 B1, issued Dec. 4, 2001, to O. Purainen, discloses a method for estimating an impulse response and a receiver in a radio system where the signal to be sent comprises a known training sequence, which receiver comprises means for sampling the received signal, and means for calculating a first estimate for the impulse response by means of the known training sequence. To enable an accurate determination of the impulse response, the receiver comprises means for making preliminary decisions on the received samples by means of the first impulse response estimate, means for calculating an error value of the estimated samples and the received samples calculated by means of the preliminary decisions, means for calculating a second estimate of the impulse response by minimizing said error value, and means for calculating a new estimate for the impulse response, by combining the first and second estimates with each other.
U.S. Pat. No. 6,275,523 B1, issued Aug. 14, 2001, to Chen et al., discloses a system for in-service nonlinearity measurements that measures such nonlinearities by way of comparing received linear error-corrected unfiltered signal samples with re-generated reference signal samples to calculate magnitude and phase nonlinear error values. Linear distortion is removed from the received signal samples in order to truly characterize nonlinear behavior of the transmitter. The linear error-corrected received signal samples are generated without applying the receiver shaping filtering. Reference signal samples are re-generated from estimated transmitted symbols from the unfiltered linear error-corrected received signal samples. The transmitted symbols are estimated using a multi-region slicer which dynamically estimates constellation decision levels from the unfiltered signal samples. A weighted, least-square based polynomial regression is performed on magnitude and phase nonlinear error values in order to estimate magnitude and phase nonlinear error functions while suppressing the impact of other non-systematic distortions.
The above cited prior art does not provide a means for accurately measuring and estimating what occurs between the excitation input produced by the acoustic transmitter and output or received response. Consequently, there remains a long felt but unsolved need for an improved means for improved techniques to determine the channel/target response function, including nonlinear effects therein. Those skilled in the art will appreciate the present invention that addresses the above and other problems.
Accordingly, it is an object of the present invention to provide an improved active sonar detection apparatus and method.
Another object of the present invention is to provide a method and apparatus to determine a channel/target nonlinear response function and/or the significance of the effect of nonlinearities in the channel/target response function.
These and other objects, features, and advantages of the present invention will become apparent from the drawings, the descriptions given herein, and the appended claims. However, it will be understood that the above listed objects and advantages of the invention are intended only as an aid in understanding aspects of the invention, and are not intended to limit the invention in any way, and do not form a comprehensive list of objects, features, and advantages.
In accordance with the present invention, a method for enhancing active sonar is provided by determining optimum detector. This includes providing a controlled excitation signal for in-water transmission of an acoustic signal and receiving a response signal produced in response to said in-water transmission of said acoustic signal. The method then calculates a Wiener/Volterra kernel from the excitation signal and response signal. Any Wiener/Volterra kernels related to random noise contributions are omitted. The optimum detector is determined by using the remaining Wiener/Volterra kernels to give an optimal correlation between the excitation signal and the response signal. Additional details are provided for determining different orders of Wiener/Volterra kernels.
The method may further comprise comparing a power of the response signal to the residual power to determine the contribution of nonlinearity to the total response signal. In a preferred embodiment, the Volterra/Wiener expansion is limited to third order using the above described remaining Wiener/Volterra kernels which are represented by the following equation:
y(t)=h0+∫dxcfx84
1h1(xcfx841)xc3x97(txe2x88x92xcfx841)+
∫∫dxcfx841dxcfx842h2(xcfx841,xcfx842)xc3x97
(txe2x88x92xcfx841)xc3x97(txe2x88x92xcfx842)+
∫∫∫dxcfx841dxcfx842dxcfx843h3(xcfx84
1,xcfx842,xcfx843)xc3x97(txe2x88x92xcfx841)xc3x97
(txe2x88x92xcfx842)xc3x97(txe2x88x92xcfx843)
The invention may also comprise a system or apparatus for active sonar detection which may comprise one or more features such as, for instance, an in-water transmitter operable to produce an excitation signal for transmission of an acoustic signal, a receiver to receive a response signal, a model for operating on the excitation signal and the response signal, and a nonlinear processor operable for computing h0, h1, h2, and h3 from the above described equation.
The nonlinear processor is preferably operable for measuring the response signal when the excitation signal is zero, for purposes of determining h0. The nonlinear processor is preferably operable for measuring the response signal while controlling the excitation signal to be real white Gaussian noise at different power factor levels to thereby compute h1. Furthermore, the nonlinear processor is operable for utilizing a correlation between the excitation signal and the response signal for determining h2. The nonlinear processor can also utilize a second correlation between the excitation signal and the response signal for determining h3. The nonlinear processor can utilize h0, h1, h2, and h3, for determining a residual power. The nonlinear processor can also compare a power of the response signal to the residual power to determine the total contribution of nonlinear components to the response signal.